## bmp db
bmpDF <- read.csv("c:/users/95218.CHARLOTTE/Documents/R/Pilot-SCM-App/bWQ BMP FlatFile BMP Indiv Anal_Rev 10-2014.csv",
stringsAsFactors=FALSE, sep=",", header=TRUE)
## IBMPDB Boxplots
pBox <- plot_ly(type = 'box') %>%
add_boxplot(y=bmpDF[which(bmpDF$Monitoring.Station.Type=="Inflow"),
"WQ.Analysis.Value"],
boxpoints = FALSE,
marker = list(color = 'rgb(7,40,89)'),
line = list(color = 'rgb(7,40,89)'),
name = "Influent") %>%
add_boxplot(y = bmpDF[which(bmpDF$Monitoring.Station.Type=="Outflow"),
"WQ.Analysis.Value"],
name = "Effluent",
boxpoints = FALSE,
marker = list(color = 'rgb(9,56,125)'),
line = list(color = 'rgb(9,56,125)'))
pBox
## Simple table
## output$boxTable0 <- renderTable({
## temp <- ibmpDataset()
## inf <- temp[which(temp$Monitoring.Station.Type=="Inflow"),]
## eff <- temp[which(temp$Monitoring.Station.Type=="Outflow"),]
## tt <- data.frame(
## Inflow=c(nrow(inf), median(inf$WQ.Analysis.Value),
## mean(inf$WQ.Analysis.Value), min(inf$WQ.Analysis.Value),
## max(inf$WQ.Analysis.Value)),
## Outflow=c(nrow(eff), median(eff$WQ.Analysis.Value),
## mean(eff$WQ.Analysis.Value), min(eff$WQ.Analysis.Value),
## max(eff$WQ.Analysis.Value)),
## row.names=c("n", "Median", "Mean", "Min.", "Max."))
## tt}, rownames=TRUE
## )
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